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edsteva.io.synthetic.utils

generate_events_before_t0 

generate_events_before_t0(
    generator: np.random.Generator,
    t_start: int,
    t_end: int,
    n_events: int,
    t0: int,
    increase_time: int,
    increase_ratio: float,
)

Generate events before t0 - increase_time / 2

PARAMETER DESCRIPTION
generator

TYPE: np.random.Generator

t_start

Starting date in seconds

TYPE: int

t_end

Ending date in seconds

TYPE: int

n_events

Number of events to generate

TYPE: int

t0

Events deployment date

TYPE: int

increase_time

Events deployment interval in seconds

TYPE: int

increase_ratio

Ratio between events before t0 and events after t0

TYPE: float

RETURNS DESCRIPTION
pd.Series

A series of datetime values representing generated events
Source code in edsteva/io/synthetic/utils.py 
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def generate_events_before_t0(
    generator: np.random.Generator,
    t_start: int,
    t_end: int,
    n_events: int,
    t0: int,
    increase_time: int,
    increase_ratio: float,
):
    """Generate events before t0 - increase_time / 2

    Parameters
    ----------
    generator : np.random.Generator
    t_start : int
        Starting date in seconds
    t_end : int
        Ending date in seconds
    n_events : int
        Number of events to generate
    t0 : int
        Events deployment date
    increase_time : int
        Events deployment interval in seconds
    increase_ratio : float
        Ratio between events before t0 and events after t0

    Returns
    -------
    pd.Series
        A series of datetime values representing generated events
    """

    t0_before = t0 - increase_time / 2
    n_before = int(
        (t0_before - t_start)
        * n_events
        / ((t0 - t_start) + increase_ratio * (t_end - t0))
    )

    return pd.to_datetime(
        pd.Series(generator.integers(t_start, t0_before, n_before)),
        unit="s",
    )

generate_events_after_t0 

generate_events_after_t0(
    generator: np.random.Generator,
    t_start: int,
    t_end: int,
    n_events: int,
    t0: int,
    increase_time: int,
    increase_ratio: float,
)

Generate events after t0 + increase_time / 2

PARAMETER DESCRIPTION
generator

TYPE: np.random.Generator

t_start

Starting date in seconds

TYPE: int

t_end

Ending date in seconds

TYPE: int

n_events

Number of events to generate

TYPE: int

t0

Events deployment date

TYPE: int

increase_time

Events deployment interval in seconds

TYPE: int

increase_ratio

Ratio between events before t0 and events after t0

TYPE: float

RETURNS DESCRIPTION
pd.Series

A series of datetime values representing generated events
Source code in edsteva/io/synthetic/utils.py 
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def generate_events_after_t0(
    generator: np.random.Generator,
    t_start: int,
    t_end: int,
    n_events: int,
    t0: int,
    increase_time: int,
    increase_ratio: float,
):
    """Generate events after t0 + increase_time / 2

    Parameters
    ----------
    generator : np.random.Generator
    t_start : int
        Starting date in seconds
    t_end : int
        Ending date in seconds
    n_events : int
        Number of events to generate
    t0 : int
        Events deployment date
    increase_time : int
        Events deployment interval in seconds
    increase_ratio : float
        Ratio between events before t0 and events after t0

    Returns
    -------
    pd.Series
        A series of datetime values representing generated events
    """

    t0_after = t0 + increase_time / 2
    n_after = int(
        increase_ratio
        * (t_end - t0_after)
        * n_events
        / ((t0 - t_start) + increase_ratio * (t_end - t0))
    )

    return pd.to_datetime(
        pd.Series(generator.integers(t0_after, t_end, n_after)),
        unit="s",
    )

generate_events_around_t0 

generate_events_around_t0(
    generator: np.random.Generator,
    t_start: int,
    t_end: int,
    n_events: int,
    t0: int,
    increase_time: int,
    increase_ratio: float,
)

Generate events between t0 - increase_time / 2 and t0 + increase_time / 2

PARAMETER DESCRIPTION
generator

TYPE: np.random.Generator

t_start

Starting date in seconds

TYPE: int

t_end

Ending date in seconds

TYPE: int

n_events

Number of events to generate

TYPE: int

t0

Events deployment date

TYPE: int

increase_time

Events deployment interval in seconds

TYPE: int

increase_ratio

Ratio between events before t0 and events after t0

TYPE: float

RETURNS DESCRIPTION
pd.Series

A series of datetime values representing generated events
Source code in edsteva/io/synthetic/utils.py 
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def generate_events_around_t0(
    generator: np.random.Generator,
    t_start: int,
    t_end: int,
    n_events: int,
    t0: int,
    increase_time: int,
    increase_ratio: float,
):
    """Generate events between t0 - increase_time / 2 and t0 + increase_time / 2

    Parameters
    ----------
    generator : np.random.Generator
    t_start : int
        Starting date in seconds
    t_end : int
        Ending date in seconds
    n_events : int
        Number of events to generate
    t0 : int
        Events deployment date
    increase_time : int
        Events deployment interval in seconds
    increase_ratio : float
        Ratio between events before t0 and events after t0

    Returns
    -------
    pd.Series
        A series of datetime values representing generated events
    """
    t0_before = t0 - increase_time / 2
    t0_after = t0 + increase_time / 2
    n_middle = int(
        (increase_time / 2)
        * (increase_ratio + 1)
        * n_events
        / ((t0 - t_start) + increase_ratio * (t_end - t0))
    )

    return pd.to_datetime(
        pd.Series(
            generator.triangular(
                left=t0_before, right=t0_after, mode=t0_after, size=n_middle
            )
        ),
        unit="s",
    )

generate_events_around_t1 

generate_events_around_t1(
    generator: np.random.Generator,
    t_start: int,
    t_end: int,
    n_events: int,
    t1: int,
    increase_time: int,
    increase_ratio: float,
)

Generate events between t1 - increase_time / 2 and t1 + increase_time / 2

PARAMETER DESCRIPTION
generator

TYPE: np.random.Generator

t_start

Starting date in seconds

TYPE: int

t_end

Ending date in seconds

TYPE: int

n_events

Number of events to generate

TYPE: int

t1

End of events deployment date

TYPE: int

increase_time

End of events deployment interval in seconds

TYPE: int

increase_ratio

Ratio between events before t1 and events after t1

TYPE: float

RETURNS DESCRIPTION
pd.Series

A series of datetime values representing generated events
Source code in edsteva/io/synthetic/utils.py 
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def generate_events_around_t1(
    generator: np.random.Generator,
    t_start: int,
    t_end: int,
    n_events: int,
    t1: int,
    increase_time: int,
    increase_ratio: float,
):
    """Generate events between t1 - increase_time / 2 and t1 + increase_time / 2

    Parameters
    ----------
    generator : np.random.Generator
    t_start : int
        Starting date in seconds
    t_end : int
        Ending date in seconds
    n_events : int
        Number of events to generate
    t1 : int
        End of events deployment date
    increase_time : int
        End of events deployment interval in seconds
    increase_ratio : float
        Ratio between events before t1 and events after t1

    Returns
    -------
    pd.Series
        A series of datetime values representing generated events
    """
    t1_before = t1 - increase_time / 2
    t1_after = t1 + increase_time / 2
    n_middle = int(
        (increase_time / 2)
        * (increase_ratio + 1)
        * n_events
        / ((t1 - t_start) * increase_ratio + (t_end - t1))
    )

    return pd.to_datetime(
        pd.Series(
            generator.triangular(
                left=t1_before, right=t1_after, mode=t1_before, size=n_middle
            )
        ),
        unit="s",
    )

generate_events_after_t1 

generate_events_after_t1(
    generator: np.random.Generator,
    t_start: int,
    t_end: int,
    n_events: int,
    t1: int,
    increase_time: int,
    increase_ratio: float,
)

Generate events after t1 + increase_time / 2

PARAMETER DESCRIPTION
generator

TYPE: np.random.Generator

t_start

Starting date in seconds

TYPE: int

t_end

Ending date in seconds

TYPE: int

n_events

Number of events to generate

TYPE: int

t1

End of events deployment date

TYPE: int

increase_time

End of events deployment interval in seconds

TYPE: int

increase_ratio

Ratio between events before t1 and events after t1

TYPE: float

RETURNS DESCRIPTION
pd.Series

A series of datetime values representing generated events
Source code in edsteva/io/synthetic/utils.py 
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def generate_events_after_t1(
    generator: np.random.Generator,
    t_start: int,
    t_end: int,
    n_events: int,
    t1: int,
    increase_time: int,
    increase_ratio: float,
):
    """Generate events after t1 + increase_time / 2

    Parameters
    ----------
    generator : np.random.Generator
    t_start : int
        Starting date in seconds
    t_end : int
        Ending date in seconds
    n_events : int
        Number of events to generate
    t1 : int
        End of events deployment date
    increase_time : int
        End of events deployment interval in seconds
    increase_ratio : float
        Ratio between events before t1 and events after t1

    Returns
    -------
    pd.Series
        A series of datetime values representing generated events
    """

    t1_after = t1 + increase_time / 2
    n_after = int(
        (t_end - t1_after) * n_events / ((t1 - t_start) * increase_ratio + (t_end - t1))
    )

    return pd.to_datetime(
        pd.Series(generator.integers(t1_after, t_end, n_after)),
        unit="s",
    )